Season 3, Episode 22: Transforming Candidate Hiring Experience with Sapia
In this episode, we talk to Barb Hyman, Founder & CEO of Sapia, the winner of ManpowerGroup’s VivaTech Challenge. Held last month, VivaTech is the biggest start-up and tech event in Europe and is recognized worldwide as a powerful catalyst for business transformation, start-up growth, and innovation for the common good.
Recognized in the “Cutting Edge Tech & Employee Experience” category, Sapia is changing the way we qualify candidates by going beyond traditional assessments to help global corporations attract and hire more diverse talent. By turning simple text conversations into talent insights, Sapia enables companies to interrupt hiring bias and provide an unforgettable candidate experience.
Hosts: Dominika Gałusa and April Clark
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Intro(00:01): The future of work and the future for workers is changing. From new technologies and talent strategies, to the management of tomorrow's workforce. Tap in to ManpowerGroup Talent Solutions’ 60 years of expertise and join us for the Transform Talent Podcast - your guide to talent market trends, new technologies and winning talent solutions.
Dominika Gałusa (00:28): Hello and welcome to the 22nd episode of the Transform Talent Podcast. We are your hosts, Dominika Galusa…
April Clark (00:36): …and April Clark. In this episode, we'd like to showcase the winner of one of our ManpowerGroup’s VivaTech challenges, Sapia AI. Held last month, VivaTech is the biggest start up and tech event in Europe and is recognized worldwide as a powerful catalyst for business transformation, start up growth, and innovation for the common good. Recognized in the Cutting Edge Tech and Employee Experience category, Sapia is changing the way we qualify candidates by going beyond traditional assessments to help global corporations attract and hire more diverse talent while reducing time and cost to hire by 90% using its proprietary automation technology.
Dominika Gałusa (01:20): To talk to us more about this exciting technology, we are joined today by Barb Hyman, Founder and CEO of Sapia. Barb, it's so nice to have you here with us.
Barb Hyman (01:30): Thanks for having me. I'm delighted to be here.
Dominika Gałusa (01:32): It's great to have you here. So, Barb, let's start at the beginning. Can you tell us a little more about Sapia. What was your inspiration?
Barb Hyman (01:41): Well, look, it's actually based on my own experience in the work environment. So I, formerly, before I was in this job and started this company, I was a CHRO for quite a few years. And what I could see in all the organizations that I worked in was just an enormous tax on the business from hiring. And particularly, the interview part of hiring. I could see that there was just a lot of bias, a lot of it unconscious. But it meant that we were really hiring what I call mirror hiring. We were continuously bringing in people who looked like us. And we were missing out on a lot of talent. And so I felt there had to be a better way to identify great people without bias in a way that didn't suck up so much time within an organization. And that was the genesis of Sapia.
And what Sapia has done for hiring is really what Steve Jobs did for the phone, which is it's tried to combine multiple functionalities into one experience. So we are the world's first smart interviewer. It combines an assessment, an interview, and feedback all in the one experience, which is a short chat conversation.
Dominika Gałusa (02:50): Thank you. Thank you for explaining that. And that was such a great story how you founded Sapia. So, winning the VivaTech Challenge is a wonderful accomplishment and speaks to the cutting edge nature of your technology. Can you tell us what makes Sapia so unique?
Barb Hyman (03:07): Yeah. Sapia is really touching on what I think people are used to in the consumer world, which is actually a really great consumer experience. You know, I think we've talked about candidate experience for a long time. But not much has really changed until Sapia has come along. What we have done is really challenged a lot of the norms around how do you engage with candidates, how do you treat candidates. What we have cornered the market on is on experience and how that enables discovery of soft skills and communication skills. So, you know, what it is is just five questions. But what really makes it powerful for the candidate is, firstly, they get to share their own story of who they are in their words. So it's very empowering. There's no time limit and so there's no pressure on the candidate to respond quickly, which can be threatening and scary for a lot of candidates. It doesn't involve any video, which can often also exclude certain types of candidates who don't feel comfortable in that format. And it's obviously built for mobile first.
But the aspect of it that really is incredible for candidates and for companies' brands is that every candidate gets feedback. So this is the difference between smart chat, which is the basis of our technology and what I would call simple chat. Which is it's not just work flow automation. But it's work flow automation that is intelligent. So from just three or 400 words, it can learn a lot about you. And we've decided that it's really important that candidates learn from the experience. So they receive six insights and coaching. And it's amazing what it does for people's motivation and self-awareness. But also how that impacts on the company's brand. So, so that's where we're particularly special for candidates.
Dominika Gałusa (04:52): And it is amazing how, you know, such a simple conversation can generate so much information. So how do you feel this type of personality assessment augments or even replaces the need for traditional skills-based resumes? And why would that be advantageous?
Barb Hyman (05:11): Look, we would say that the CV is really, you know, on its way out as a tool or as a data set for understanding people. Because a CV has a lot of limitations. One, you know, anyone can game a CV in terms of what they choose to put on it. And a lot of smart graduates do that now to try and make it through the CV passes. But a CV is really just an inventory of your work experience and your educational experience. And in that respect, it can really be used in a way which advantages privileged people and disadvantages those who don't have the right degree or the right school on their CV. I like to think that the CV is a bit of a proxy for advantage. And so it's a quite a biased tool for understanding talent and it doesn't reveal anything of who you are as a person.
You know, the fact that you worked at a certain place or that you completed a degree doesn't really tell us whether you're a great critical thinker, or you're someone that is really open to new experiences, or you're someone that's gonna lead and inspire teams. You know, those soft skills, which I think are really the life skills that a lot of organizations are looking for now, are what are truly revealed by our technology, which you cannot find in a CV.
So, you know, we would say this is definitely replacing the CV, but going much further than that in terms of how it removes bias in understanding someone's true potential.
April Clark (06:34): Barb, you know, with more companies focusing on inclusivity and fairness, it seems that Sapia has entered the market in such an important time. And you've touched a little bit on how the technology can remove bias. But I'd love to hear more about, you know, Natural Language Processing and fair profiling in the use with Sapia.
Barb Hyman (06:52): Yeah. So Natural Language Processing is not something new. Um, you know, it’s been around for quite a while. It's something that's used every day in our normal life. Like when we go and search on Google Maps, and when we're typing into Google and it predicts what we're gonna say next. Alexa, you know, all of these tools are really based on NLP. And it's a- it's probably the fastest growing area of AI globally. You know, Google has something like 10,000 PhDs working just in Natural Language Processing. So it's a very fast moving technology area to work with. And that's the way that we've chosen to build our assessment, which is based on language which is the core of NLP.
And the reason why our technology has been able to interrupt bias is, firstly, that we don't use any personal data, any demographic data in our algorithms where we're trying to understand your soft skills from the conversation. We might capture that data through the experience so that we can conduct bias testing at the company level, but none of that data makes it into the AI. So, you know, in contrast to, say, video which does use quite a lot of visual data and can create the risk of, of bias, you know, that's a great starting point to have.
The second is that we also have what's called an optimizer algorithm. It's a bit technical. But it basically means that fairness is a constraint before algorithm can be deployed, before any model can be deployed. So that you will never have, when you're using Sapia, a predictive model which is unfair with respect to gender and ethnicity. And you can add in any other information as well when it comes to disability and age, if we have that data, to also make sure it's, you know, it's never unfair with respect to that cohort. So that's incredibly powerful, to be able to deliver that.
And then in our dashboard, you can actually see that. So one of the things that we think is really important when you're using AI around people is transparency. How do you make transparent what's going on within the technology? And in our dashboard you can see, transparently, what the machine is doing. You can also see what the humans are doing, which is often where you can see the bias coming through. And that creates trust. You know, trust in the technology, trust in the system, trust at the candidate level and at the, um, a hiring manager level. So those are some of the ways in which we've ensured that it is a technology that removes bias rather than amplifies bias.
April Clark (09:17): That's amazing. You know, we've seen AI integration become a priority across so many various industries over the years, including talent platforms. For our listeners who are still learning more about AI, can you tell us the difference between NLP and AI?
Barb Hyman (09:34): Yeah. Sometimes I think it's helpful to use analogies. AI works like you're learning to ride a bike. You know, you don't tell your child to move their left foot in a circle on the left pedal in the forward direction while moving your right foot in a circle. You just put them on, give them a push, and tell them to keep it upright and go forward. And that's very much how AI works. They might fall a few times, but they're honing their skills each time they fail.
What NLP does is it uses human language, human linguistics, to understand people. And in order to get you from one end to the other. So the power of language has long been understood in the context of personality assessment. If you go back to the origins of psychometric assessment, it all started with language and what's called lexical hypothesis. So we're not using a, um, an input that is unknown to the assessment world. But we're bringing the, the innovations and the machine processing power of NLP to there so that we can do that in a few seconds. And we can do that discovering an enormous amount from that short conversation.
You know, when you think about answering a simple SJT, a multi-choice questionnaire, you know, there's not a lot of variants that you're capturing between the three of us, say, if we were all answering the same experience. It's very limited. We're just picking one of three options across 150 questions. Whereas when we're all answering a question like tell us about a time that you leaned in to solve a difficult problem and what did you learn? We're gonna give such completely different answers. And that variance is what drives the predictive power and the insight that comes from using NLP. So that's, that's the innovation that allows you to do it in just five questions not, you know, 150 or 400 questions that you would typically have to do in a traditional assessment.
April Clark (11:24): Those are great examples, Barb. Thank you so much. I think it always helps to make sure that it- we know the technical terms and the analogies were spot on. Thank you.
Dominika Gałusa (11:34): Barb, changing the gear slightly, I'd like to talk more about the value of using Sapia. Mm, for example, what does the profiling and matching say about the hiring company? How is it giving advice back to the organization?
Barb Hyman (11:50): Yeah. So I'm a big believer that, you know, again, on the principle of transparency and really empowering people to make better decisions. So what you see when you use our technology on the recruiter side is you see, obviously, a match score to the profile. But you also see why. So you can click down and understand what are the strengths of that person, what are their gaps? You can read their responses. So in the world of GDPR obviously it's really important to give candidates the right to have their assessment reviewed by a human. So a recruiter can review that and consider whether or not, you know, they would come to the same conclusion. It gives you data-driven interview questions. So at this point, when you're actually interviewing the candidate after they've gone through- gone through this initial process, it allows you to be really smart and hone in on those areas that are most important.
So the whole intent is that very quickly and very intuitively, as a recruiter, you feel smarter to make the right decision, to ask the right questions. You understand how that person is gonna fit into your team. Because in every organization, context really matters. You know, you need to see someone's profile and consider that in the context of not just the role, but the team, and the culture. And so that intelligence is power to the- in the hands of the recruiter and the hiring manager. So that, that- that side of it is really, I think, you know, the most empowering for the organization. I think just giving a score doesn't really give you much confidence to trust the technology. You need to explain why someone was scored in the way they do.
Dominika Gałusa (13:23): These are such important aspects you're mentioning. So building on the value Sapia can bring to companies, Barb, your solution is already in use around the world. Do you have a favorite success story you can share?
Barb Hyman (13:36): Well, look, we're starting to work with Manpower now on a really interesting use case. You know, I think we all know that whilst there are two billion workers in the world, it's very hard to find them and a lot of workers don't have the ready skills, particularly on the technical side. And, uh, you know, there are quite amazing strategies that are being considered now to build capability globally, but build capability within organizations for, for technical roles.
And one of the partnerships that we're embarking on with Manpower is to use our technology to discover undiscovered talent in the US amongst the lower socioeconomic cohorts. So people who don't go to college. People who don't have the kind of privileges that many of us do in terms of education. You know, there are three million students that graduate from high school every year in the US. You know, how do you use this technology to understand which of those, you know, at scale in a really empowering experience could be trained into tech workers? So that is incredibly exciting. Because the opportunity to give people a chance at a life and at a career that they wouldn't otherwise have, because Sapia can see that potential, is, you know, really amazing for us as a business and as a team. So that's something that we're starting to work on with Manpower.
But we have other clients where the impact on diversity has been really powerful as well, that we're very proud of. So a business in Ireland called Woody's who have tried for years to really improve the diversity of their hires and have not been able to even though there's been a lot of positive intent. And in three months, they saw a three times increase in hiring of ethnic minorities and also had feedback from people who self-identified as transgender that they just felt really comfortable with the whole experience of applying for a job because it's blind, because it's untimed. And they got to share who they are and they felt like they were really being valued for who they are not for what sits on a CV or, you know, the color of their skin or their gender. So those kinds of impact stories are, you know, super powerful for us.
April Clark (15:42): And I'm sure a big part of why you were the winner at VivaTech, Barb. Those are great stories. Uh, and it's, it's impressive to see the impact that Sapia's having. You know, the technology itself is already so advanced. But I'd like to take a minute to look into the future. How do you see Sapia evolving or even obliterating the role of the recruiter?
Barb Hyman (16:03): Yeah. I don't know that I'd use the word obliterating. But I think really we're here to augment human intelligence. I think that's where AI is most powerful. You know, there's a lot of hysteria around AI replacing humans. But you can see in industries where AI is taking traction, like even just booking a flight. You know, we can all go online now and use Expedia and other tools to do that. But yet, you know, there are still businesses that are thriving that provide, you know, travel agents, to help people, you know, from a concierge perspective.
I think what it means, bringing in this technology, is the role of the recruiter is really completely redefined. You know, they're liberated from the very monotonous, repeatable processes like screening CVs or screening people on the phone. You know, I think their job is about being in the business and understanding the business needs and understanding the team that they're hiring into and what success will look like. So I see, for recruiters, it's about becoming talent advisors and talent concierges. And if you're not spending, you know, 80% of your time in the business then I think you're probably gonna miss out in terms of that transition.
You know, I think AI won't replace recruiters, but I think recruiters who use AI will replace recruiters that don't use AI.
April Clark (17:18): That makes sense. What do you see, I guess, in that new world? What does that future of talent acquisition look like?
Barb Hyman (17:25): Look, I think, you know, it's so, um, there's a- uh, it's basically transformative. You know, when I was in HR no one joined HR to work with technology. You joined HR to work with people. And now, you know, the number one asset, if you like, in an HR team is someone who understands data and the power of data and how data can help you drive towards better decision making, fairer decision making, more insight for people making those decisions. And so that requires a completely different talent pool, a completely different way of designing, you know, what the role of HR and talent acquisition is.
I also think that we're moving to a world where hybrid is here forever. And, you know, we're never going back to a world before COVID. And so how do you create connection between applicant and organization? You know, how do you help people really understand the culture? And technology is gonna play a huge role in that. So one of the things that we also find companies are really embracing about Sapia is that you really get to share your story as a company. Because we can put anything into a chat. You can have, you know, me record a video as a hiring manager and explain what my team's about and what I'm looking for and what's important to me. And so that ability to really have a personalized journey through an application process using Sapia and smart technology is amazing.
You know, we have personalized journeys in our consumer life every day. And we take that for granted. But it's taken a long time to get that into the, the world of hiring. And, you know, now it's here.
Dominika Gałusa (18:58): These are very thoughtful insights, Barb. And, you know, it was wonderful to have you here today on our 22nd episode of the Transform Talent Podcast. I hope that our listeners enjoyed learning about Sapia as much as we did.
April Clark (19:13): And to all our listeners, don't forget to subscribe and leave us a review on your favorite podcast listening app. See you next episode.
Outro (19:23): The Transform Talent Podcast, because we know the right talent transforms organizations and helps your business flourish. Talent Solutions, business and talent aligned.